AI developer jobs · Boston

AI developer openings in Boston: Python, LLM, GenAI, full stack, and apprenticeships.

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  • Logo Google DeepMind
    Healthcare AI Engineer
    Google DeepMind 4.5 · 200 reviews

    Healthcare AI engineer role in Boston — validated models, privacy-preserving training, and clinical workflow integration for US health partners.

    Healthcare AI engineerClinical MLHIPAAPython
    Boston, MAHybrid
    $155k – $215k / year
    Easy applyFull-time16 applicants
    Posted Oct 1, 2026Quick preview

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AI developer jobs in Boston — 2026 overview

The AI developer market in Boston (Massachusetts) stays competitive: LLM, RAG, agents, MLOps, and GenAI in product. Employers want Python, Java, or full-stack profiles who ship to production—not just prototypes.

On Ganloss, listings focus on the AI ecosystem: scale-ups, consultancies, finance, and enterprise transformation. Posted salary ranges help you compare before applying.

Skills employers expect

Common stack: Python, PyTorch or TensorFlow, LLM APIs (OpenAI, Anthropic), LangChain/LlamaIndex, Docker/Kubernetes, SQL, and cloud (AWS, GCP). Enterprise GenAI also hires full-stack Java/Angular profiles.

Recruiters value production skills (tests, observability, latency), product collaboration, and agile delivery. Apprenticeships and internships remain strong entry paths.

How to apply effectively

Create your Ganloss profile, turn on email alerts, and target posts with salary shown. Bring a portfolio (GitHub, RAG/agent projects) and tune your résumé for LLM, MLOps, Python, GenAI.

FAQ

How many AI developer jobs in Boston on Ganloss?
0 open listings right now. Create an alert so you do not miss new posts.
What salary for an AI developer in Boston?
Ganloss median: $120–175k/year (mid full-time). Junior: ~$95–125k · Senior LLM/MLOps: ~$165–220k in major metros.
Do you need an engineering degree to become an AI developer?
A CS degree helps, but recruiters prioritize shipped projects, production experience, and Python/ML depth. Bootcamps and apprenticeships complement self-taught paths.
AI developer vs data scientist?
AI developers build software, APIs, and deployment pipelines. Data scientists explore data and train models. ML engineer roles sit in between.